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AananditaKatreMastersThesisJuly2017.pdf (3.47 MB)

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Developing Methods for Prediction and Reduction of Springback using a Practical Method to Estimate E-Modulus

Katre, Aanandita Ramakant
http://rave.ohiolink.edu/etdc/view?acc_num=osu1500028074848847

Abstract Details

2017, Master of Science, Ohio State University, Mechanical Engineering.
Bending operations such as U-bending, hat bending, V-bending etc. are commonly used operations in the sheet metal forming industry. Springback is one of the most difficult and important challenges to forming good quality parts in these operations, especially for materials like Advanced High Strength Steels, Copper and Aluminum. Currently, dies are modified and re-cut three to five times in the industry to compensate for springback and ensure part quality. Improving the accuracy of prediction and reduction of springback would reduce the time and cost for die development and tryout. Existing mathematical models for springback prediction are complicated and require various material parameters that are difficult or expensive to obtain. This study aims to develop a simple method for accurate prediction and reduction of springback in the U-bending and Wipe bending processes. Experiments were carried out for U-bending of AHSS and Aluminum using Shiloh die and S shaped die and wipe bending of Copper alloy using a die designed at CPF. The materials were bent to different angles. Simulations were carried out using DEFORM and PAM-STAMP for same conditions as experiments. The springback results of simulation and experiments were compared and inverse analysis was carried out to find the value of apparent E-moduli that would accurately predict the springback in different materials for the different bending angles. Experiments were conducted to investigate the effect of ram speed and ram motion on springback of AHSS and Aluminum alloys in the U-bending process. Simulations were conducted in PAM-STAMP to study the effect of variation of pad force on springback in U-bending with crunching operation. Inverse analysis was successfully applied to predict springback accurately in different materials with different part geometries. An apparent E-modulus vs strain curve was developed which can be input to FE software for the analysis of forming operations and springback. Ram speed and ram motion do not have significant impact on springback. The pad force was varied to successfully obtain an optimum value that would eliminate springback in the U-bending with crunching operation of AHSS.
Dr. Taylan Altan (Advisor)
Dr. Blaine Lilly (Committee Member)
115 p.
Engineering; Mechanical Engineering
U-bending; Wipe bending; L-bending; Inverse Analysis; S-die; Springback; AHSS; Advanced high strength steels; pad force; variation;

Recommended Citations

Citations

  • Katre, A. R. (2017). Developing Methods for Prediction and Reduction of Springback using a Practical Method to Estimate E-Modulus [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1500028074848847

    APA Style (7th edition)

  • Katre, Aanandita Ramakant. Developing Methods for Prediction and Reduction of Springback using a Practical Method to Estimate E-Modulus. 2017. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1500028074848847.

    MLA Style (8th edition)

  • Katre, Aanandita Ramakant. "Developing Methods for Prediction and Reduction of Springback using a Practical Method to Estimate E-Modulus." Master's thesis, Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1500028074848847

    Chicago Manual of Style (17th edition)

osu1500028074848847
487
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This open access ETD is published by The Ohio State University and OhioLINK.